CiNii Articles - machine learning

1

Identification method of network traffic unlikely belonging to target users by machine learning using application-identifying firewall log [in Japanese]

市之瀬樹生 , 佐藤聡 , 新城靖 , 三宮秀次 , 星野厚

インターネットと運用技術シンポジウム論文集 (2019), 9-16, 2019-11-28

IPSJ
2

An Attempt to Read Network Traffic with Doc2vec

Mamoru Mimura

… To address this problem, neural networks can be applied to perform feature learning. … To address this problem, neural networks can be applied to perform feature learning. …

情報処理学会論文誌 60(11), 2019-11-15

IPSJ
3

Towards Finding a Solution for Collectible Card Games with Counterfactual Regret Minimization

Haoyu Zhang , Yoshimasa Tsuruoka

ゲームプログラミングワークショップ2019論文集 (2019), 235-241, 2019-11-01

IPSJ
4

Eﬀectivity of Densely Multi Layer Perceptron and Eﬀectivity of Features Obtained from Positions in Machine Learning Mahjong Players [in Japanese]

藤田竜貴 , 松崎公紀

ゲームプログラミングワークショップ2019論文集 (2019), 213-220, 2019-11-01

IPSJ
5

An Eﬃcient Reinforcement Learning Method Using Prediction Errors Between Models [in Japanese]

橋本大世 , 鶴岡慶雅

ゲームプログラミングワークショップ2019論文集 (2019), 136-143, 2019-11-01

IPSJ
6

An Extension of Counterfactual Regret Minimization for Multiplayer Card Games

Yu Cao , Tomoyuki Kaneko

ゲームプログラミングワークショップ2019論文集 (2019), 28-33, 2019-11-01

IPSJ
7

Prediction of Plasma Etching Yields by Machine Learning [in Japanese]

木野日織 , 幾世和将 , DAM Hieu Chi , 浜口智志

プラズマ・核融合学会誌 = Journal of plasma and fusion research 95(11), 542-547, 2019-11
8

AI Now : Machine Learning [in Japanese]

神嶌敏弘 , 鹿島久嗣

人工知能 : 人工知能学会誌 : journal of the Japanese Society for Artificial Intelligence 34(6), 905-915, 2019-11
9

Emotion and AI [in Japanese]

日永田智絵 , 堀井隆斗 , 長井隆行

人工知能 : 人工知能学会誌 : journal of the Japanese Society for Artificial Intelligence 34(6), 881-887, 2019-11
10

Advancing Machine Learning and Probabilistic Modeling [in Japanese]

麻生英樹 , 松尾豊 , 中原啓貴

人工知能 : 人工知能学会誌 : journal of the Japanese Society for Artificial Intelligence 34(6), 804-810, 2019-11
11

Development of risk prediction models based on machine learning techniques for multifactorial disorder [in Japanese]

重水大智 , 角田達彦

内分泌・糖尿病・代謝内科 = Endocrinology, diabetology & metabolism 49(5), 363-366, 2019-11
12

Automated machine learning for identification of pest aphid species (Hemiptera: Aphididae)

Hayashi Masayuki , Tamai Kazuhiko , Owashi Yuta , Miura Kazuki

Applied entomology and zoology 54(4), 487-490, 2019-11
13

Investigating the Impacts of Customer Experience and Attribute Performances on Overall Ratings using Online Review Data: Nonlinear Estimation and Visualization with a Neural Network

Sato Toshikuni

DSSR Discussion Papers (105), 1-45, 2019-11

IR
14

Real-Time Silent Speech BCI with Japanese Hiragana (福祉情報工学)

GABORIT Sylvain , YAMAZAKI Toshimasa

電子情報通信学会技術研究報告 = IEICE technical report : 信学技報 119(251), 75-80, 2019-10-26
15

Toward the development personal and on-demand weather forecasting devices : measurement of the spectrum of the sky [in Japanese]

田中晴康 , 大寺康夫

電気学会研究会資料. EMC = The papers of technical meeting on electromagnetic compatibility, IEE Japan 2019(33-51), 77-81, 2019-10-24
16

Toward the development personal and on-demand weather forecasting devices : measurement of the spectrum of the sky [in Japanese]

田中晴康 , 大寺康夫

電子情報通信学会技術研究報告 = IEICE technical report : 信学技報 119(242), 169-173, 2019-10-24
17

Toward the development personal and on-demand weather forecasting devices : measurement of the spectrum of the sky [in Japanese]

田中晴康 , 大寺康夫

電子情報通信学会技術研究報告 = IEICE technical report : 信学技報 119(243), 169-173, 2019-10-24
18

Consideration of input data in person recognition by gait using Extreme Learning Machine [in Japanese]

紅谷颯杜 , 安達雅春

電子情報通信学会技術研究報告 = IEICE technical report : 信学技報 119(238), 55-60, 2019-10-22
19

Consideration of input data in person recognition by gait using Extreme Learning Machine [in Japanese]

紅谷颯杜 , 安達雅春

電子情報通信学会技術研究報告 = IEICE technical report : 信学技報 119(237), 55-60, 2019-10-22
20

Verification of the Usefulness of Personal Authentication with Aerial Input Numerals Using Leap Motion

Yamamoto Shun , Ito Momoyo , Ito Shin-ichi , Fukumi Minoru

… We collect numerals 0 to 9 from five subjects, then apply three pre-processing to these data, learn and authenticate them by CNN (convolutional neural network) which is a method of machine learning. … As a result of learning, an average authentication accuracy was 92.4%. …

Advances in Science, Technology and Engineering Systems Journal 4(5), 369-374, 2019-10-22

IR

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